Solved

Exhibit 17

Question 42

Multiple Choice

Exhibit 17.2.To examine the differences between salaries of male and female middle managers of a large bank,90 individuals were randomly selected and the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) ,
Educ = the number of years of education,
Exper = the number of months of experience,
Train = the number of weeks of training,
Gender = the gender of an individual;1 for males,and 0 for females.
Also,the following Excel partial outputs corresponding to the following models are available:
Model A: Salary = β0 + β1Educ + β2Exper + β3Train + β4Gender + ε Exhibit 17.2.To examine the differences between salaries of male and female middle managers of a large bank,90 individuals were randomly selected and the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) , Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual;1 for males,and 0 for females. Also,the following Excel partial outputs corresponding to the following models are available: Model A: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Train + β<sub>4</sub>Gender + ε Model B: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Gender + ε Refer to Exhibit 17.2.Using Model B,what is the regression equation found by Excel for males? A) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender B) = 5322.5011 + 139.5366Educ + 3.3488Expe C) = 4713.2506 + 139.5366Educ + 3.3488Expe D) Model B: Salary = β0 + β1Educ + β2Exper + β3Gender + ε Exhibit 17.2.To examine the differences between salaries of male and female middle managers of a large bank,90 individuals were randomly selected and the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) , Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual;1 for males,and 0 for females. Also,the following Excel partial outputs corresponding to the following models are available: Model A: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Train + β<sub>4</sub>Gender + ε Model B: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Gender + ε Refer to Exhibit 17.2.Using Model B,what is the regression equation found by Excel for males? A) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender B) = 5322.5011 + 139.5366Educ + 3.3488Expe C) = 4713.2506 + 139.5366Educ + 3.3488Expe D) Refer to Exhibit 17.2.Using Model B,what is the regression equation found by Excel for males?


A) Exhibit 17.2.To examine the differences between salaries of male and female middle managers of a large bank,90 individuals were randomly selected and the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) , Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual;1 for males,and 0 for females. Also,the following Excel partial outputs corresponding to the following models are available: Model A: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Train + β<sub>4</sub>Gender + ε Model B: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Gender + ε Refer to Exhibit 17.2.Using Model B,what is the regression equation found by Excel for males? A) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender B) = 5322.5011 + 139.5366Educ + 3.3488Expe C) = 4713.2506 + 139.5366Educ + 3.3488Expe D) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender
B) Exhibit 17.2.To examine the differences between salaries of male and female middle managers of a large bank,90 individuals were randomly selected and the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) , Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual;1 for males,and 0 for females. Also,the following Excel partial outputs corresponding to the following models are available: Model A: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Train + β<sub>4</sub>Gender + ε Model B: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Gender + ε Refer to Exhibit 17.2.Using Model B,what is the regression equation found by Excel for males? A) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender B) = 5322.5011 + 139.5366Educ + 3.3488Expe C) = 4713.2506 + 139.5366Educ + 3.3488Expe D) = 5322.5011 + 139.5366Educ + 3.3488Expe
C) Exhibit 17.2.To examine the differences between salaries of male and female middle managers of a large bank,90 individuals were randomly selected and the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) , Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual;1 for males,and 0 for females. Also,the following Excel partial outputs corresponding to the following models are available: Model A: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Train + β<sub>4</sub>Gender + ε Model B: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Gender + ε Refer to Exhibit 17.2.Using Model B,what is the regression equation found by Excel for males? A) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender B) = 5322.5011 + 139.5366Educ + 3.3488Expe C) = 4713.2506 + 139.5366Educ + 3.3488Expe D) = 4713.2506 + 139.5366Educ + 3.3488Expe
D) Exhibit 17.2.To examine the differences between salaries of male and female middle managers of a large bank,90 individuals were randomly selected and the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) , Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual;1 for males,and 0 for females. Also,the following Excel partial outputs corresponding to the following models are available: Model A: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Train + β<sub>4</sub>Gender + ε Model B: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Gender + ε Refer to Exhibit 17.2.Using Model B,what is the regression equation found by Excel for males? A) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender B) = 5322.5011 + 139.5366Educ + 3.3488Expe C) = 4713.2506 + 139.5366Educ + 3.3488Expe D)

Correct Answer:

verifed

Verified

Unlock this answer now
Get Access to more Verified Answers free of charge

Related Questions

Q19: The number of dummy variables representing a

Q35: Quantitative variables assume meaningful _, whereas qualitative

Q37: For the logistic model,the predicted values of

Q37: For the model y = β0 +

Q40: For the linear probability model y =

Q41: Exhibit 17.2.To examine the differences between salaries

Q44: Exhibit 17.2.To examine the differences between salaries

Q45: Exhibit 17.1.A researcher has developed the following

Q46: Exhibit 17.2.To examine the differences between salaries

Q47: Consider the model y = β0 +

Unlock this Answer For Free Now!

View this answer and more for free by performing one of the following actions

qr-code

Scan the QR code to install the App and get 2 free unlocks

upload documents

Unlock quizzes for free by uploading documents